---
title: Intraday Volatility Forecasting for Indian Stocks
url: https://www.ml-quant.com/papers/repec/ids-ijecbr-v-27-y-2024-i-4-p-633-650/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:ids:ijecbr:v:27:y:2024:i:4:p:633-650
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.inderscience.com%2Flink.php%3Fid%3D138879%3Bh%3Drepec%3Aids%3Aijecbr%3Av%3A27%3Ay%3A2024%3Ai%3A4%3Ap%3A633-650
featured: 2024-06-20
citations: unknown
topic: Derivatives & Volatility
---


# Intraday Volatility Forecasting for Indian Stocks

The paper evaluates the effectiveness of range-based volatility estimations against standard models using Indian stock market data, concluding that range-based models are superior and the GKYZ volatility estimator is the most accurate.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.inderscience.com%2Flink.php%3Fid%3D138879%3Bh%3Drepec%3Aids%3Aijecbr%3Av%3A27%3Ay%3A2024%3Ai%3A4%3Ap%3A633-650
- Identifier: RePEc:ids:ijecbr:v:27:y:2024:i:4:p:633-650
- Released: 2024-06-20
- First featured: Quant Letter No. 54 (2024-06-20): https://www.ml-quant.com/issues/2024-06-20/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

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